1. Field of the Invention
This invention relates generally to an industrial process, and, more particularly, to adjusting a sampling protocol of processed workpieces in an adaptive semiconductor process.
2. Description of the Related Art
There is a constant drive within the semiconductor industry to increase the quality, reliability and throughput of integrated circuit devices, e.g., microprocessors, memory devices, and the like. This drive is fueled by consumer demands for higher quality computers and electronic devices that operate more reliably. These demands have resulted in a continual improvement in the manufacture of semiconductor devices, e.g., transistors, as well as in the manufacture of integrated circuit devices incorporating such transistors. Additionally, reducing the defects in the manufacture of the components of a typical transistor also lowers the overall cost per transistor as well as the cost of integrated circuit devices incorporating such transistors.
Generally, a set of processing steps is performed on a group of wafers, sometimes referred to as a “lot,” using a variety of processing tools, including photolithography steppers, etch tools, deposition tools, polishing tools, rapid thermal processing tools, implantation tools, etc. The technologies underlying semiconductor processing tools have attracted increased attention over the last several years, resulting in substantial improvements.
One technique for improving the operation of a semiconductor processing line includes using a factory wide control system to automatically control the operation of the various processing tools. The manufacturing tools communicate with a manufacturing framework or a network of processing modules. Each manufacturing tool is generally connected to an equipment interface. The equipment interface is connected to a machine interface that facilitates communications between the manufacturing tool and the manufacturing framework. The machine interface can generally be part of an Advanced Process Control (APC) system. The APC system initiates a control script based upon a manufacturing model, which can be a software program that automatically retrieves the data needed to execute a manufacturing process. Often, semiconductor devices are staged through multiple manufacturing tools for multiple processes, generating data relating to the quality of the processed semiconductor devices.
During the fabrication process, various events may take place that affect the performance of the devices being fabricated. That is, variations in the fabrication process steps result in device performance variations. Factors, such as feature critical dimensions, doping levels, particle contamination, film optical properties, film thickness, film uniformity, etc., all may potentially affect the end performance of the device. Various tools in the processing line are controlled in accordance with performance models to reduce processing variation. Commonly controlled tools include photolithography steppers, polishing tools, etching tools, and deposition tools, etc. Pre-processing and/or post-processing metrology data is supplied to process controllers for the tools. Operating recipe parameters, such as processing time, are calculated by the process controllers based on the performance model and the metrology data to attempt to achieve post-processing results as close to a target value as possible. Reducing variation in this manner leads to increased throughput, reduced cost, higher device performance, etc., all of which equate to increased profitability.
Run-to-run control in semiconductor manufacturing is a type of batch control, where a batch may be as small as one wafer or as large as several lots of wafers. The standard output of a run-to-run controller is a process recipe. This recipe defines the set points for “low-level” controllers built into the processing tool. The process recipe is generally calculated based on an estimated “process” state (e.g., the processing tool state, wafer state, etc.) and a process model that is substantially representative of the operation of the process. The “process” state is typically not measured directly but rather estimated based on the measurements from previously processed wafers. Based on at least the process model and the estimated process state, the run-to-run controller supervises the processing tool by specifying required values for process variables such as temperature, pressure, flow, and process time. The processing tool initiates the activities necessary to maintain these variables at the requested values.
In an adaptive process, the process model or parameters used to determine the next recipe may be adjusted, as desired, based on metrology data associated with previously processed workpieces to bring the actual process results closer to the target results. It may be desirable to adjust the process model or parameters, for example, if the controller is unable to achieve the desired results because of disturbance or process changes. Because the process model or parameters are adjusted based on the metrology data, the amount of metrology data that is available may affect how reliably the process model/parameters may be adjusted. Thus, if a system employing a fixed sampling frequency plan measures a fixed number of wafers, then the amount of metrology data that is available also remains fixed. In a fixed sampling frequency plan, for example, only one out of every five processed wafers may be measured because of time and cost concerns. A fixed sampling frequency plan thus may not offer an efficient or flexible plan for adjusting the process model or parameters to achieve the desired process results.
The present invention is directed to overcoming, or at least reducing the effects of, one or more of the problems set forth above.